Abstract
Although three-dimensional, immersive virtual worlds, such as Active Worlds, Second Life, and Teleplace have been in existence for several years, their organizational use is rather limited. This paper posits, perhaps counter intuitively, that the diffusion of virtual worlds within organizations could be enhanced by their recreational usage. This argument is motivated by the notion developed in this paper that the use of technologies need not remain within a single context, but instead can cross-contexts, for example from recreational to vocational. We term such shift cross-context IS continuance. This paper proposes that workers using virtual worlds for recreational (i.e., hedonic and social) use are suitably positioned to discover those technologies’ workplace applicability, thereby assisting in their diffusion within the organization. Building on the supporting results of an empirical study, this paper recommends that managers consider allowing for ‘playtime’ with virtual worlds as a mechanism for enhancing their adoption and subsequent diffusion in the workplace. From an information systems (IS)-research perspective, this paper makes several important contributions. First, it contributes to the IS continuance literature by arguing for, and providing evidence in support of, the existence of cross-context continuance. To date, this literature stream has examined only one aspect of continuance – for example, within-context. Second, this paper identifies recreational and work as distinct dimensions of technology usage, and hedonic and social usage as sub-dimensions of the former, thereby contributing to the contextualization of this core IS construct. Third, it is one of the early field studies dedicated to the empirical examination of virtual worlds.
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Notes
Applicable technologies are capable of offering multiple uses in various contexts (Dearing and Meyer, 1994).
Objects created by human workmanship (Merriam-Webster Dictionary and Oxford Dictionary).
Sun Microsystems’ 3D virtual world.
Although the inner-workings of within-context IS continuance are beyond the scope of this paper, it is worth noting that there are several explanations for this link including automatic behavior or habit (e.g. Limayem et al., 2007; Limayem and Cheung, 2008; Ortiz de Guinea and Markus, 2009), formation or changes of cognitive beliefs (e.g. Karahanna et al., 1999; Venkatesh et al., 2002; Kim and Malhotra, 2005), and formation or changes of attitudes (e.g. Bhattacherjee, 2001a, 2001b; Bhattacherjee and Premkumar, 2004). For a detailed review of the various approaches to IS continuance behavior see recent review by Ortiz de Guinea and Markus (2009).
According to the group's public profile, it is a ‘community for professionals involved in the virtual worlds and 3D Internet industry.’
Web surveys work best when targeted to a well-defined interest group on a question of self-interest (Doane and Seward, 2010), such as the LinkedIn group we targeted.
Two respondents indicated that they are not currently employed; we did not use their responses in the data analyses.
We acknowledge that given the paucity of empirical research on virtual worlds, the content validity of the scales could be enhanced in future research.
In a separate analysis, we tested a comparable model using the approach of repeated indicators (Chin et al., 2003) and have obtained similar results.
Respondents were provided with a text box in which they could enter their comments and/or feedback.
Past research has established a link between intentions to use and actual future use behavior (Davis et al., 1989).
‘Playtime’ has been shown as conducive to inventive behavior in past studies (e.g., Weick, 1998; Cooper, 2000). Indeed, organizations such as Apple and Google provide their employees with play spaces to foster and encourage innovation and creativity (Gilkey and Kilts, 2007).
International Business Machines (IBM) Corp.: http://domino.research.ibm.com/comm/research_projects.nsf/pages/virtualworlds.IBMVirtualWorldGuidelines.html; SUN Microsystems Inc.: http://www.sun.com/communities/guidelines.jsp; Intel Corporation: http://www.intel.com/sites/sitewide/en_US/social-media.htm; Utah State: http://www.utahta.wikispaces.net/file/view/State+of+Utah+Social+Media+Guidelines+9.29.pdf/177053623/State%20of%20Utah%20Social%20Media%20Guidelines%209.29.pdf.
In addition to developing new items for existing scales, it may be fruitful to develop new scales altogether. For example, it is possible that educational usage of a virtual world would emerge as a distinct usage context, meriting a new scale (an interesting example is Global Kids’ Teen Second Life).
References
Agarwal, R. and Karahanna, E. (2000). Time Flies When you're Having Fun: Cognitive absorption and beliefs about information technology usage, MIS Quarterly 24 (4): 665–694.
Agarwal, R. and Prasad, J. (1997). The Role of Innovations Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies, Decision Sciences 28 (3): 557–582.
Ahuja, M.K. and Thatcher, J.B. (2005). Moving Beyond Intentions and Toward the Theory of Trying: Effects of work environment and gender on post-adoption information technology use, MIS Quarterly 29 (3): 427–459.
Babin, B.J., Darden, W.R. and Griffin, M. (1994). Work and/or Fun: Measuring hedonic and utilitarian shopping value, Journal of Consumer Research 20: 656–664.
Backer, T.E. (2000). Finding the Balance: Program Fidelity and Adaptation in Substance Abuse Prevention Report, Center for Substance Abuse Prevention, Washington DC.
Bagozzi, R.P. (2011). Measurement and Meaning in Information Systems and Organizational Research: Methodological and philosophical foundations, MIS Quarterly 35 (2): 261–292.
Bagozzi, R.P., Yi, Y. and Phillips, L.W. (1991). Assessing Construct Validity in Organizational Research, Administrative Science Quarterly 36 (3): 421–448.
Bhattacherjee, A. (2001a). Understanding Information Systems Continuance: An expectation-confirmation model, MIS Quarterly 25 (3): 351–370.
Bhattacherjee, A. (2001b). An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance, Decision Support Systems 32 (2): 201–214.
Bhattacherjee, A. and Premkumar, G. (2004). Understanding Changes in Belief and Attitude Toward Information Technology Usage: A theoretical model and longitudinal test, MIS Quarterly 28 (2): 229–254.
Bollen, K.A. (2011). Evaluating Effect, Composite, and Causal Indicators in Structural Equation Models, MIS Quarterly 35 (2): 359–372.
Bowman, D.M.J.S., Balch, J.K., Artaxo, P., Bond, W.J., Carlson, J.M., Cochrane, M.A., D'Antonio, C.M., DeFries, R.S., Doyle, J.C., Harrison, S.P., Johnston, F.H., Keeley, J.E., Krawchuk, M.A., Kull, C.A., Marston, J.B., Moritz, M.A., Prentice, I.C., Roos, C.I., Scott, A.C., Swetnam, T.W., van der Werf, G.R. and Pyne, S.J. (2009). Fire in the Earth System, Science 342: 481–484.
Brown, S.A. and Venkatesh, V. (2005). Model of Adoption of Technology in Households: A baseline model test and extension incorporating household life cycle, MIS Quarterly 29 (3): 399–426.
Burton-Jones, A. and Straub Jr., D.W. (2006). Reconceptualizing System Usage: An empirical approach and empirical test, Information Systems Research 17 (3): 228–246.
Chin, W.W. (1998). Issues and Opinion on Structural Equation Modeling, MIS Quarterly 22 (1): 7–16.
Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and Electronic-Mail Emotion/Adoption Study, Information Systems Research 14 (2): 189–217.
Cooper, R.B. (2000). Information Technology Development Creativity: A case study of attempted radical change, MIS Quarterly 24 (2): 245–276.
Davis, A., Murphy, J., Owens, D., Khazanchi, D. and Zigurs, I. (2009). Avatars, People, and Virtual Worlds: Foundations for research in metaverses, Journal of the AIS 10 (2): 90–117.
Davis, F.D., Bagozzi, R.P. and Warsaw, P.R. (1989). User Acceptance of Computer Technology: A comparison of two theoretical models, Management Science 35 (8): 982–1003.
Dearing, J.W. and Meyer, G. (1994). An Exploratory Tool for Predicting Adoption Decisions, Science Communication 16 (1): 43–57.
Deng, L., Turner, D.E., Gehling, R. and Prince, B. (2010). User Experience, Satisfaction, and Continual Usage Intention of IT, European Journal of Information Systems 19 (1): 60–75.
Dennis, A., Wixom, B.H. and Vandernberg, R.J. (2001). Understanding Fit and Appropriation Effects in Group Support Systems via Meta-analysis, MIS Quarterly 25 (2): 167–193.
DeSanctis, G. and Poole, M.S. (1994). Capturing the Complexity in Advanced Technology Use – Adaptive structuration theory, Organization Science 5 (2): 121–147.
Diamantopoulos, A. and Winklhofer, H.M. (2001). Index Construction with Formative Indicators: An alternative to scale development, Journal of Marketing Research 38 (2): 269–278.
Dillman, D.A. (1999). Mail and Internet Surveys: The tailored design method, New York: John Wiley Company.
Doane, D.P. and Seward, L.E. (2010). Applied Statistics in Business & Economics, 3rd edn, New York: McGraw Hill.
Dreher, C., Reiners, T., Dreher, N. and Dreher, H. (2009). Virtual Worlds as a Context Suited for Information Systems Education: Discussion of pedagogical experience and curriculum design with reference to second life, Journal of Information Systems Education 20 (2): 211–224.
Ein-Dor, P. and Segev, E. (1993). A Classification of Information Systems: Analysis and interpretation, Information Systems Research 4 (2): 166–204.
Eschenbrenner, B.F., Nah, F-H. and Siau, K. (2008). 3-D Virtual Worlds in Education: Applications, benefits, issues, and opportunities, Journal of Database Management 19 (4): 91–110.
Fornell, C. and Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and statistics, Journal of Marketing Research 18 (3): 382–388.
Fuller, R.M. and Dennis, A.R. (2009). Does Fit Matter? The impact of task-technology fit and appropriation on team performance in repeated tasks, Information Systems Research 20 (1): 2–17.
Gilkey, R. and Kilts, C. (2007). Cognitive Fitness, Harvard Business Review 85: 53–66.
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2009). Multivariate Data Analysis, 7th edn, Upper Saddle River, NJ: Prentice Hall.
Hauser, M. (2009). Origin of the Mind, Scientific American 301 (3): 44–51.
Hirschman, E.C. and Holbrook, M.B. (1982). Hedonic Consumption: Emerging concepts, methods, and propositions, Journal of Marketing 46: 92–101.
Holbrook, M.B. and Hirschman, E.C. (1982). The Experiential Aspects of Consumption: Consumer fantasies, feelings, and fun, Journal of Consumer Research 9: 132–140.
Hong, S., Kim, J. and Lee, H. (2008). Antecedents of Use-Continuance in Information Systems: Toward and integrative view, Journal of Computer Information Systems 48 (3): 61–73.
Hong, S.-J. and Tam, K.Y. (2006). Understanding the Adoption of Multipurpose Information Appliances: The case of Mobile Data Services, Information Systems Research 17 (2): 162–179.
Ives, B. and Junglas, I. (2008). APC Forum: Business implications of virtual worlds and serious gaming, MIS Quarterly Executive 7 (3): 151–156.
Jarvis, C.B., MacKenzie, S.B. and Podsakoff, P.M. (2003). A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research, Journal of Consumer Research 30 (2): 199–218.
Jasperson, J., Carter, P.E. and Zmud, R.W. (2005). A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems, MIS Quarterly 29 (3): 525–557.
Karahanna, E., Straub, D.W. and Chervany, N.L. (1999). Information Technology Adoption Across Time: A cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly 23 (2): 183–213.
Kettinger, W.J. and Grover, V. (1997). The Use of Computer-Mediated Communication in an Organizational Context, Decision Sciences 28 (3): 513–555.
Kim, S.S. and Malhotra, N.K. (2005). A Longitudinal Model of Continued IS Use: An integrative view of four mechanisms underlying postadoption phenomena, Management Science 51 (5): 741–755.
Kock, N. (2008). E-Collaboration and E-Commerce in Virtual Worlds: The potential of second life and world of warcraft, International Journal of E-Collaboration 4 (3): 1–13.
LaBrosse, M. (2008). Managing Virtual Teams, Employment Relations Today 35 (2): 81–86.
Limayem, M. and Cheung, C.M.K. (2008). Understanding Information Systems Continuance: The case of internet-based learning technologies, Information and Management 45 (4): 227–232.
Limayem, M., Hirt, S.G. and Cheung, C.M.K. (2007). How Habit Limits the Predictive Power of Intention: The case of information systems continuance, MIS Quarterly 31 (4): 705–737.
MacKenzie, S.B., Podsakoff, P.M. and Podsakoff, N.P. (2011). Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating new and existing techniques, MIS Quarterly 35 (2): 293–334.
McCrae, R.R. and Costa Jr., P.T. (1983). Social Desirability Scales More Substance than Style, Journal of Consulting and Clinical Psychology 5 (1): 882–888.
Messinger, P.R., Stroulia, E., Lyons, K., Bone, M., Niu, R.H., Smirnov, K. and Perelgut, S. (2009). Virtual Worlds – Past, present, and future: New directions in social computing, Decision Support Systems 47 (3): 204–228.
Mittal, B. (1987). A Framework for Relating Consumer Involvement to Lateral Brain Functioning, Advances in Consumer Research 14: 41–45.
Orlikowski, W.J. (2000). Using Technology and Constituting Structures: A practice lens for studying technology in organizations, Organization Science 11 (4): 404–428.
Ortiz de Guinea, A. and Markus, M.L. (2009). Why Break the Habit of a Lifetime? Rethinking the roles of intention, habit, and emotion in continuing information technology use, MIS Quarterly 33 (3): 433–444.
Overby, E. (2008). Process Virtualization Theory and the Impact of Information Technology, Organization Science 19 (2): 277–292.
Parameswaran, M. and Whinston, A.B. (2007). Research Issues in Social Computing, Journal of the AIS 6: 336–350.
Petter, S., Straub, D. and Rai, A 2007. Specifying Formative Constructs in Information Systems Research, MIS Quarterly 31 (4): 623–656.
Podsakoff, P., MacKenzie, S.B., Lee, J. and Podsakoff, N. (2003). Common Method Biases in Behavioral Research: A critical review of the literature and recommended remedies, Journal of Applied Psychology 88: 879–903.
Pollitt, D. (2008). Learn-While-You-Play Programme Gets IBM Recruits Up to Speed, Training & Management Development Methods 22 (1): 401–403.
Rogers, E. (2003). Diffusion of Innovations, 5th edn, New York, NY: Free Press.
Salancik, G.R. and Pfeffer, J. (1977). An Examination of Need-Satisfaction Models of Job Attitudes, Administrative Science Quarterly 22: 427–456.
Salisbury, D., Chin, W.W., Gopal, A. and Newsted, P.R. (2002). Research Report: Better theory through measurement – Developing a scale to capture consensus on appropriation, Information Systems Research 13 (1): 91–105.
Shang, R-A., Chen, Y-C. and Shen, L. (2005). Extrinsic Versus Intrinsic Motivations for Consumers to Shop Online, Information & Management 42: 401–413.
Straub, D., Boudreau, M-C. and Gefen, D. (2004). Validation Guidelines for IS Positivist Research, Communications of the AIS 13: 380–427.
Torrence, R. (2008). Thinking Big about Small Tools, Archeological Papers of the American Anthropological Association 12 (1): 179–189.
Trevino, L.K. and Webster, J. (1992). Flow in Computer-Mediated Communication: Electronic mail and voice mail evaluation and impacts, Communication Research 19 (5): 539–573.
Van der Heijden, H. (2004). User Acceptance of Hedonic Information Systems, MIS Quarterly 28 (4): 695–704.
Venkatesh, V. and Brown, S.A. (2001). A Longitudinal Investigation of Personal Computers in Homes: Adoption determinants and emerging challenges, MIS Quarterly 25 (1): 71–102.
Venkatesh, V., Brown, S.A., Maruping, L.M. and Bala, H. (2008). Predicting Different Conceptualizations of System Use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectations, MIS Quarterly 32 (3): 483–502.
Venkatesh, V., Speier, C. and Morris, M.G. (2002). User Acceptance Enablers in Individual Decision Making About Technology: Toward an integrated model, Decision Sciences 33 (2): 216–297.
Wakefield, R. and Whitten, D. (2006). Mobile Computing: A user study on hedonic/utilitarian mobile device usage, European Journal of Information Systems 15: 292–300.
Weick, K.E. (1998). Improvisation as a Mindset for Organizational Analysis, Organization Science 9 (5): 543–555.
Wild, T.C., Kuiken, D. and Schopflocher, D. (1995). The Role of Absorption in Experiential Involvement, Journal of Personality and Social Psychology 69 (3): 569–579.
Wixom, B.H. and Todd, P.A. (2005). A Theoretical Integration of User Satisfaction and Technology Acceptance, Information Systems Research 16 (1): 85–102.
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Nevo, S., Nevo, D. & Kim, H. From recreational applications to workplace technologies: an empirical study of cross-context IS continuance in the case of virtual worlds. J Inf Technol 27, 74–86 (2012). https://doi.org/10.1057/jit.2011.18
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DOI: https://doi.org/10.1057/jit.2011.18